Videography has grown in popularity and implementation, and the demand for high-quality video has continued to increase. For example, automobiles use cameras for extra safety features, manufacturers use vision systems for quality control and automation, surgeons use small cameras for minimally invasive procedures, and mobile phones often have one or more cameras capable of video capture.
High dynamic range (HDR) video delivers imagery in a wide range of light intensities found in real scenes, ranging from sunlight to dark shadows. This gives HDR video more of a true brightness which can significantly enhance viewers' experience. However, HDR video can require significant post-processing, and combining frames can be computationally intensive. Further, when a scene has significant motion, capturing the scene may require a short exposure time that has motion aliasing and captures less light (resulting in a poor signal-to-noise ratio), and processing may require de-blurring efforts that can be difficult and prone to artifacts.
High-speed cameras have been useful for capturing high quality video, as they can be used to record fast-moving objects as an image onto a storage medium (e.g., using a charge-coupled device (CCD) or CMOS active pixel sensor), with a high number (e.g., greater than 1000) of frames per second. These are typically transferred onto DRAM for storage. However, high-speed cameras can be very expensive and complex. For example, it can be difficult to implement high-speed cameras in portable devices such as mobile telephones. While traditional video cameras can be relatively less expensive and easier to implement, such cameras often use a constant full-frame exposure time for each pixel and do not provide enough frames per second to create quality high-speed video. These and other problems have been challenging to the implementation of high-quality video capture.